This RO1 application seeks to conduct fine mapping and association studies under a region of significant linkage to endometriosis identified in a large collaborative study. Endometriosis is a complex gynecologic disorder affecting up to 10% of women, an estimated 5.5 million women in the US alone. In endometriosis, endometrial tissue is found outside the uterus, growing, bleeding cyclically arid causing adhesions. Common symptoms are severe pelvic pain, painful menstrual periods and infertility. The disorder often recurs and has a major impact on women's health, relationships, productivity and life choices. Genetic factors contribute to endometriosis, and this study's long-term objective is to identify genetic variants predisposing women to the disorder. DNA samples were obtained from 1,221 affected sister pair (ASP) and 1,616 triad (case plus both parent) families. DNA is also available from 950 unrelated cases and 950 controls. All affected women were diagnosed during pelvic surgery. A 10-cM genome scan, completed in 1,176 ASP families, has identified significant linkage to chromosome 10, with evidence for two distinct susceptibility loci. [unreadable] [unreadable] The project aims to identify susceptibility genes by genotyping single nucleotide polymorphisms (SNPs) in 286 genes within our region of significant linkage and tagging SNPs at a density of approximately 10 Kb across the region. We will initially test for association using a case control design, with cases drawn from the ASP families in which the initial linkage was identified and unrelated controls, using Illumina SNP genotyping technology. SNPs showing association with endometriosis will be further tested by conducting replication studies in independent cases and controls using Sequenom MALDI-TOF mass spectrometry. Variants showing significant association in the replication sample, together with adjacent SNPs, will be genotyped in ASP and triad families to control for population stratification and conduct joint linkage: linkage disequilibrium analysis to identify SNP associations accounting for the linkage signal. Knowledge of the susceptibility genes in endometriosis will lead to better diagnosis and more targeted treatments based upon a clearer understanding of the aberrant cellular and molecular mechanisms. [unreadable] [unreadable] [unreadable]